at Capgemini
ConsultanciesPosted 5 days ago
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**MLOps Engineer**: Design, build, and manage end-to-end MLOps pipelines for AI/ML model production. Collaborate with cross-functional teams to implement CI/CD, automate releases, and ensure model performance, scalability, security, and observability. Required skills: 4+ years in MLOps, Python, ML/DL frameworks (TensorFlow, PyTorch), MLOps platforms (MLflow, Kubeflow), CI/CD tools, cloud platforms (AWS, Azure, GCP), Docker, Kubernetes, Git. Needs strong problem-solving and stakeholder management skills.
- Compensation
- Not specified
- City
- Pune
- Country
- India
Currency: Not specified
Full Job Description
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way youd like, where youll be supported and inspired by a collaborative community of colleagues around the world, and where youll be able to reimagine whats possible. Join us and help the worlds leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Your Role
- Design, build, and manage end-to-end MLOps pipelines to deploy, monitor, and scale AI/ML models in production environments.
- Collaborate with Data Scientists, AI Engineers, and Software Development teams to operationalize machine learning, NLP, and Generative AI solutions.
- Develop and maintain infrastructure for model training, validation, deployment, monitoring, and automated retraining.
- Implement CI/CD and automation frameworks to accelerate model releases while ensuring reliability and governance.
- Manage containerized and cloud-based deployments using technologies such as Docker, Kubernetes, AWS, Azure, and GCP.
- Drive model performance, scalability, security, and observability through continuous monitoring, optimization, and troubleshooting.
Your Profile
- 4+ years of hands-on experience deploying and managing Machine Learning models in production environments.
- Strong expertise in Python and ML/DL frameworks such as TensorFlow, PyTorch, and scikit-learn, along with MLOps platforms like MLflow, Kubeflow, or TFX.
- Experience implementing CI/CD pipelines using tools such as Jenkins, GitLab CI, or similar DevOps technologies.
- Solid understanding of cloud platforms (AWS, Azure, GCP), containerization (Docker), orchestration (Kubernetes), and version control systems (Git).
- Excellent problem-solving, communication, and stakeholder management skills, with the ability to work effectively across cross-functional teams.
What you will love at capgemini
- Opportunity to work on cutting-edge AI, Generative AI, Machine Learning, and cloud transformation programs for global clients.
- Collaborative and inclusive work environment that encourages innovation, learning, and knowledge sharing.
- Access to industry-leading technologies, cloud platforms, and modern MLOps ecosystems.
- Continuous learning opportunities through certifications, technical academies, and career development programs.
- Exposure to large-scale enterprise AI implementations, enabling you to make a real business impact.
- Flexible and people-centric culture focused on growth, well-being, and long-term career progression.
Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Make it real | www.capgemini.com
